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Record W4285043521 · doi:10.22215/etd/2022-15068

Urban Agritecture: Inherited and Contemporary Strategies for the Canadian Landscape

2022· dissertation· en· W4285043521 on OpenAlexaboutno aff
Ambra Del Frate

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureAgricultureTechnological revolutionGeographyAgricultural revolutionEconomic geographyEnvironmental planningEngineeringArchitectural engineeringEnvironmental ethicsEconomyArchaeologyEconomics

Abstract

fetched live from OpenAlex

Historically, both architecture and agriculture have been cornerstones of social and technological advancement, insofar as developments in these areas have permitted humans to cast their gaze beyond the fulfillment of basic needs such as shelter and nourishment. Past agricultural revolutions - spurred by events like the invention of the plow, or the development of crop rotation - have heralded the beginning of new eras. Today, the immense advancements in genetics of the past two decades place us yet again at a crossroads. Standing at the cusp of a fourth agricultural revolution, where may we expect these advancements to lead us socially, and therefore spatially? This thesis seeks to address the interconnected nature of architecture and agriculture, and to determine how recent technological developments in farming could shape the future spaces we inhabit. Building on new technologies and ancient wisdom, a new prototype for the future of agriculture-optimized urban housing is proposed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0280.020
Scholarly communication0.0100.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.220
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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